Storage optimization isn’t just a data problem, it’s an application issue if storage latency degrades app performance. As many as 61 percent of companies say faster app and IT service delivery are significant initiatives. 1 Yet core to both of those goals is data availability, and legacy storage can be a hindrance that leads to costly application downtime if storage reliability isn’t addressed.

It was server insufficiency effecting compute and storage capacity that contributed to the July 2018 Amazon Prime day glitches that resulted in performance issues that left consumers unable to process their transactions. A mad scramble to manually add servers to meet traffic demand ensued, but the damage had already been done.2

Fix the App Data Gap Problem

The application impact of storage latency has immediate consequences as users expect best-in-class performance to support workflows. Unfortunately, too many companies fall short of reliable storage volumes. Half of employees say they lose 10 percent of their workday waiting for software to load — and IT decision-makers lose as many as 30 minutes a day because of application delays. As many as 40 percent of business users say the avoid using application that runs too slowly.3

So what can be done to prevent these issues? Companies should look to optimize storage volumes for application reliability by identifying storage performance issues before they can impact users. Typically, this would be a daunting challenge as 54 percent of storage problems exist outside of storage, hiding within configuration, interoperability, host, compute, VM and other issues — all of which can be costly to mitigate manually.4 Today, new storage innovations powered by artificial intelligence (AI) software are automating the process. For example, HPE InfoSight is AI software that’s integrated within HPE Nimble Storage, powered by Intel® Xeon® Scalable processors. It makes easy work of storage optimization by leveraging machine learning and predictive analytics to:

Predict and prevent downtime: Insights from analytic data is leveraged to find and fix 86 percent of storage problems before they occur — including problems that arise outside of storage, within the infrastructure stack.4

Automate support: Level one and two support problems are entirely automated, requiring no manual intervention, greatly reducing the time IT staff needs to spend on storage tasks. Level three problems that are elevated can be diagnosed faster because of analytics and global visibility into storage volumes.

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